MODELING OF THE CONTROL AND MONITORING SYSTEM OF THE PIPELINE SECTION IN THE ASPEN HYSYS PROGRAM
DOI:
https://doi.org/10.31471/1993-9981-2023-1(50)-81-92Keywords:
virtual model of a pipeline system; automated control and management system; Aspen HYSYS.Abstract
The paper examines the challenges of creating a virtual model of a pipeline system in Aspen HYSYS, taking into account physical parameters, components, technological processes, and constraints. The obtained dynamic characteristics of the model can be used to investigate the adequacy of the model and validate its behavior under real conditions. It is also necessary to study the sensitivity of the model to parameter changes and disturbances. The task is to ensure a high level of model adequacy and effective regulation of the technological parameters of the pipeline system. Based on the results of the analysis, improvements and enhancements to the model can be proposed to achieve stability, accuracy, and optimal process performance. The ultimate goal is the development of an automated control system based on the created model of the pipeline system in Aspen HYSYS. The material discusses the need for improving pipeline systems in the context of transporting various substances. It emphasizes the importance of efficiency, safety, and reliability of these systems in light of increasing transport volumes, compliance with safety standards, and environmental requirements. The material also highlights the role of efficient management of technological processes and the use of automated control and monitoring systems to ensure optimal operating parameters of the system. Considering the obtained dynamic characteristics and research results, such systems can provide effective regulation of the technological parameters of the pipeline system. Overall, this material underscores the relevance of enhancing pipeline systems to ensure their highest productivity, safety, and stability. Modeling and simulation in Aspen HYSYS allow for conducting simulations of the system's operation with various configurations and enable virtual experiments to investigate the impact of variable parameters and evaluate process outcomes.
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